MétaCan
Menu
Back to cohort
Record W7144340951 · doi:10.15083/00072992

Identification of factors enhancing the novelty of ideas in innovation workshops and their utilization for Workshop design

2015· dissertation· en· W7144340951 on OpenAlexfundno aff
恩英 金

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2015
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
FundersDepartment of Industry and Science, Australian GovernmentAustralian GovernmentGovernment of the United KingdomMinistry of Business, Innovation and EmploymentNew Zealand GovernmentGovernment of OntarioU.S. Department of State
KeywordsIdentification (biology)NoveltyKey (lock)Work (physics)

Abstract

fetched live from OpenAlex

In response to the social needs for innovation, many academic institutions all over the world have established educational programs to promote innovation focusing on the creation of new ideas.Innovation in this study is not only confined to the conventional conception of technologydriven innovation but also applies to the creation of any kind of value to human life, through introducing novel ideas, methods, directions, opportunities, and solutions that meet new requirements, through more effective products, processes, services, and technologies that are readily available to users.Reflecting this increasing need for human-centered innovation, the University of Tokyo provides innovation workshop programs to generate new ideas.To design an education program for encouraging innovative idea creation, it is crucial to formulate an evaluation method for the appropriateness of ideas generated, as well as to identify factors that encourage an appropriate idea generation.However, despite numerous previous studies on idea generation, existing definitions of the indicators for evaluation are too general to establish an evaluation method in a general context.The existing methods of evaluation on new ideas are based on subjective judgements of a certain number of raters and their evaluations vary widely, depending on the personal perception of raters.In addition, there is lack of consensus on the factors which enable us to generate appropriate ideas in spite of numerous studies in creativity education.In this study, there are three main objectives: 1) To propose an evaluation method for appropriateness of ideas by excluding subjective judgements as far as possible; 2) To identify factors which enhance appropriateness of ideas in innovation workshops; 3) To utilize this data to propose a workshop design for enhancing appropriateness in idea generation.The focus of the innovation workshops in this study is placed on the generation of ideas using analogical thinking.Analogical thinking has been identified as one of the key mechanisms for creative thinking by many researchers in the fields of cognitive psychology, cognitive science, artificial intelligence, learning science, creative research, and so on.Analogical thinking is a basic mechanism inspiring creative tasks, in which people transfer information from well-known domains and utilize it in a new domain in order to develop new ideas.In this regard, using analogical thinking for innovation workshops is required to facilitate idea generation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.310
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInstitutional Repositories DataBase (IRDB)Same topicInnovative Approaches in Technology and Social DevelopmentFrench-language works237,207